In this paper, we introduce EventKG+BThttp://eventkg-biographies.l3s.uni-hannover.de – a system that enables exploration of personal biographies based on concise biography timelines.
In [1]}, we have shown how to automatically extract biography timelines from EventKG, an event-centric and temporal knowledge graph [2]}, using a distant supervision approach.
In this approach, we trained an SVM classifier to predict the relevance of the potential timeline entries to a biography.
We obtained training data through the mapping of facts extracted from biographical articles
to the temporal relations in the EventKG knowledge graph.
